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Lecture Notes in Computer Science (including subseries Lectu...

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Preface

Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2022年 13214 LNCS卷 v页

作者： Panda, Dhabaleswar K. Sullivan, Michael Department of Computer Science and Engineering The Ohio State University ColumbusOH United States Material Science and Chemistry A*STAR Institute of High Performance Computing Singapore Singapore

Resilience of Quantum Key Distribution Source Against Laser-Damage Attack by a Variety of Lasers

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Resilience of Quantum Key Distribution Source Against Laser-...

Conference on Lasers and Electro-Optics Europe (CLEO EUROPE)

作者： Daria Ruzhitskaya Irina Zhluktova Anastasiya Ponosova Daniil Trefilov Poompong Chaiwongkhot Anqi Huang Vladimir Kamynin Vadim Makarov Russian Quantum Center Skolkovo Moscow Russia NTI Center for Quantum Communications National University of Science and Technology MISiS Moscow Russia Prokhorov General Physics Institute of Russian Academy of Sciences Moscow Russia MIREA - Russian Technological University Moscow Russia Vigo Quantum Communication Center University of Vigo Vigo Spain Department of Physics Faculty of Science Mahidol University Bangkok Thailand State Key Laboratory of High Performance Computing Institute for Quantum Information College of Computer Science and Technology National University of Defense Technology Changsha China Shanghai Branch National Laboratory for Physical Sciences at Microscale CAS Center for Excellence in Quantum Information University of Science and Technology of China Shanghai People's Republic of China

ISBN: (纸本)9798350345995

Quantum key distribution (QKD) systems provide quantum-safe key exchange. Therefore, complete security analysis of implementations of QKD protocols is in the focus of interest of a worldwide information-security community. For today, a number of QKD loopholes are closed by countermeasures, which are also considered in emerging QKD security evaluation and certification [1]–[3]. However, new threats to practical QKD implementations are still found, such as the laser-damage attack, which is a powerful hacking strategy. In investigations, CW laser radiation is most often used, but in contrast to it, the interaction of pulsed laser radiation with optical materials may lead to a wide range of effects, like nonlinear effects, dielectric breakdown, etc.

关键词： Fiber optic components high power lasers Nonlinear effects Optical materials Quantum key distribution Quantum key distribution networks

high order semi-implicit WENO schemes for all mach full euler system of gas dynamics

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arXiv 2021年

作者： Boscarino, Sebastiano Qiu, Jing-Mei Russo, Giovanni Xiong, Tao Department of Mathematics and Computer Science University of Catania Catania95127 Italy Department of Mathematics University of Delaware NewarkDE19716 United States School of Mathematical Sciences Fujian Provincial Key Laboratory of Mathematical Modeling and High-Performance Scientific Computing Xiamen University Fujian Xiamen361005 China

In this paper, we propose a new high order semi-implicit scheme for the all Mach full Euler equations of gas dynamics. Material waves are treated explicitly, while acoustic waves are treated implicitly, thus avoiding severe CFL restrictions for low Mach flows. high order accuracy in time is obtained by semi-implicit temporal integrator based on the IMEX Runge-Kutta (IMEX-RK) framework. high order in space is achieved by finite difference WENO schemes with characteristic-wise reconstructions adapted to the semi-implicit IMEX-RK time discretization. Type A IMEX schemes are constructed to handle not well-prepared initial conditions. Besides, these schemes are proven to be asymptotic preserving and asymptotically accurate as the Mach number vanishes for well-prepared initial conditions. Divergence-free property of the time-discrete schemes is proved. The proposed scheme can also well capture discontinuous solutions in the compressible regime, especially for two dimensional Riemann problems. Numerical tests in one and two space dimensions will illustrate the effectiveness of the proposed schemes. © 2021, CC BY.

关键词： Mach number

An Epitrochoidal Rotary Reactor for Solar-Driven Hydrogen Production Based on the Redox Cycling of Ceria: Thermodynamic Analysis and Optimization

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SSRN

SSRN 2022年

作者： Wang, Bo Li, Xian Zhu, Xuancan Wang, Yuesen Tian, Tian Dai, Yanjun Wang, Chi-Hwa Singapore138602 Singapore NUS Environmental Research Institute National University of Singapore Singapore138602 Singapore Department of Systems Science Institute of High Performance Computing A*STAR Singapore138632 Singapore School of Mechanical Engineering Shanghai Jiao Tong University 800 Dongchuan Road Shanghai200240 China Sloan Automotive Laboratory Mechanical Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Department of Chemical and Biomolecular Engineering National University of Singapore Singapore117585 Singapore

A novel epitrochoidal rotary reactor was proposed to perform efficient solardriven water-splitting based on thermochemical redox cycling of ceria. This study is focused on the geometry optimization of the epitrochoidal rotary reactor to achieve the optimal thermodynamic solar-to-fuel energy conversion efficiency. The mathematical descriptions of kinematic synthesis of the conjugate rotor and stator profiles are derived in detail. The geometric compression ratio is statistically estimated using a hit-or-miss Monte Carlo method. A thermodynamic model considering the solid and gas phase heat recovery is developed to evaluate the performance of the epitrochoidal rotary reactors in various geometries. Among all geometrical parameters instigated, the cam-to-rotor size ratio and the number of rotor sides are found to have the most significant impact on the solar-to-fuel energy conversion efficiency. The optimal design of the epitrochoidal rotary reactor with a curved triangle rotor offers a geometrical compression ratio of 13 and a solar-to-fuel efficiency of 17% under a concentrated solar radiative flux of 3000 suns. © 2022, The Authors. All rights reserved.

关键词： Thermoanalysis

Investigating Polarization characteristics of GRB 200503A and GRB 201009A

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arXiv 2024年

作者： Saraogi, Divita Bala, Suman Joshi, Jitendra Iyyani, Shabnam Bhalerao, Varun Aditya, J. Venkata Svinkin, D.S. Frederiks, D.D. Lysenko, A.L. Ridnaia, A.V. Kozyrev, A.S. Golovin, D.V. Mitrofanov, I.G. Litvak, M.L. Sanin, A.B. Chattopadyay, Tanmoy Gupta, Soumya Waratkar, Gaurav Bhattacharya, Dipankar Vadawale, Santosh Dewangan, Gulab Department of Physics Indian Institute of Technology Bombay Maharashtra Mumbai400076 India Science and Technology Institute Universities Space Research Association HuntsvilleAL35805 United States Inter University Centre for Astronomy and Astrophysics Maharashtra Pune411007 India School of Physics Indian Institute of Science Education and Research Thiruvananthapuram695551 India Centre of High Performance Computing Indian Institute of Science Education and Research Thiruvananthapuram695551 India Department of Computer Science and Engineering Indian Institute of Technology Bombay Powai Maharashtra Mumbai400076 India Ioffe Institute Polytekhnicheskaya 26 St. Petersburg194021 Russia 84/32 Profsoyuznaya Moscow117997 Russia Kavli Institute of Particle Astrophysics and Cosmology 452 Lomita Mall StanfordCA94305 United States Astrophysical Science Division Homi Bhabha National Institute Anushakti Nagar Maharashtra Mumbai400094 India Department of Physics Ashoka University Haryana Sonepat131029 India Physical Research Laboratory Gujarat Ahmedabad380009 India

We present results of a comprehensive analysis of the polarization characteristics of GRB 200503A and GRB 201009A observed with the Cadmium Zinc Telluride Imager (CZTI) on board AstroSat. Despite these GRBs being reasonably bright, they were missed by several spacecraft and had thus far not been localized well, hindering polarization analysis. We present positions of these bursts obtained from the Inter-Planetary Network (IPN) and the newly developed CZTI localization pipeline. We then undertook polarization analyses using the standard CZTI pipeline. We cannot constrain the polarization properties for GRB 200503A, but find that GRB 201009A has a high degree of polarization. © 2024, CC BY.

关键词： Gamma rays

AstroMLab 1: Who Wins Astronomy Jeopardy!?

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arXiv 2024年

作者： Ting, Yuan-Sen Nguyen, Tuan Dung Ghosal, Tirthankar Pan, Rui Arora, Hardik Sun, Zechang de Haan, Tijmen Ramachandra, Nesar Wells, Azton Madireddy, Sandeep Accomazzi, Alberto Research School of Astronomy & Astrophysics Australian National University Cotter Rd. WestonACT2611 Australia School of Computing Australian National University ActonACT2601 Australia Department of Astronomy The Ohio State University ColumbusOH43210 United States The Ohio State University ColumbusOH43210 United States Department of Computer and Information Science University of Pennsylvania PhiladelphiaPA19104 United States National Center for Computational Sciences Oak Ridge National Laboratory Oak RidgeTN37831 United States Department of Computer Science and Engineering Hong Kong University of Science and Technology Kowloon Hong Kong Indian Institute of Technology Patna Bihar Bihta801106 India Department of Astronomy MongManWai Building Tsinghua University Beijing100084 China Institute of Particle and Nuclear Studies High Energy Accelerator Research Organization Ibaraki Tsukuba305-0801 Japan Ibaraki Tsukuba305-0801 Japan Computational Science Division Argonne National Laboratory LemontIL60439 United States Mathematics and Computer Science Division Argonne National Laboratory LemontIL60439 United States Center for Astrophysics Harvard & Smithsonian CambridgeMA02138 United States

We present a comprehensive evaluation of proprietary and open-weights large language models using the first astronomy-specific benchmarking dataset. This dataset comprises 4,425 multiple-choice questions curated from the Annual Review of Astronomy and Astrophysics, covering a broad range of astrophysical topics.a) Our analysis examines model performance across various astronomical subfields and assesses response calibration, crucial for potential deployment in research environments. Claude-3.5-Sonnet outperforms competitors by up to 4.6 percentage points, achieving 85.0% accuracy. For proprietary models, we observed a universal reduction in cost every 3-to-12 months to achieve similar score in this particular astronomy benchmark. open-weights models have rapidly improved, with LLaMA-3-70b (80.6%) and Qwen-2-72b (77.7%) now competing with some of the best proprietary models. We identify performance variations across topics, with non-English-focused models generally struggling more in exoplanet-related fields, stellar astrophysics, and instrumentation related questions. These challenges likely stem from less abundant training data, limited historical context, and rapid recent developments in these areas. This pattern is observed across both open-weights and proprietary models, with regional dependencies evident, highlighting the impact of training data diversity on model performance in specialized scientific domains. Top-performing models demonstrate well-calibrated confidence, with correlations above 0.9 between confidence and correctness, though they tend to be slightly underconfident. The development for fast, low-cost inference of open-weights models presents new opportunities for affordable deployment in astronomy. The rapid progress observed suggests that LLM-driven research in astronomy may become feasible in the near future. © 2024, CC BY.

关键词： Astrophysics

Astromlab 1: Who Wins Astronomy Jeopardy!?

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SSRN

SSRN 2024年

作者： Ting, Yuan-Sen Nguyen, Tuan Dung Ghosal, Tirthankar Pan, Rui Arora, Hardik Sun, Zechang de Haan, Tijmen Ramachandra, Nesar Wells, Azton Madireddy, Sandeep Accomazzi, Alberto Research School of Astronomy & Astrophysics Australian National University Cotter Rd. WestonACT2611 Australia School of Computing Australian National University ActonACT2601 Australia Department of Astronomy The Ohio State University ColumbusOH43210 United States The Ohio State University ColumbusOH43210 United States Department of Computer and Information Science University of Pennsylvania PhiladelphiaPA19104 United States National Center for Computational Sciences Oak Ridge National Laboratory Oak RidgeTN37831 United States Department of Computer Science and Engineering Hong Kong University of Science and Technology Kowloon Hong Kong Indian Institute of Technology Patna Bihar Bihta801106 India Department of Astronomy Tsinghua University MongManWai Building Beijing100084 China Institute of Particle and Nuclear Studies High Energy Accelerator Research Organization Ibaraki Tsukuba305-0801 Japan Ibaraki Tsukuba305-0801 Japan Computational Science Division Argonne National Laboratory LemontIL60439 United States Mathematics and Computer Science Division Argonne National Laboratory LemontIL60439 United States Center for Astrophysics Harvard & Smithsonian CambridgeMA02138 United States

We present a comprehensive evaluation of proprietary and open-weights large language models using the first astronomy-specific benchmarking dataset. This dataset comprises 4,425 multiple-choice questions curated from the Annual Review of Astronomy and Astrophysics, covering a broad range of astrophysical topics. Our analysis examines model performance across various astronomical subfields and assesses response calibration, crucial for potential deployment in research environments. Claude-3.5-Sonnet outperforms competitors by up to 4.6 percentage points, achieving 85.0% accuracy. For proprietary models, we observed a universal reduction in cost every 3-to-12 months to achieve similar score in this particular astronomy benchmark. open-weights models have rapidly improved, with LLaMA-3-70b (80.6%) and Qwen-2-72b (77.7%) now competing with some of the best proprietary models. We identify performance variations across topics, with non-English-focused models generally struggling more in exoplanet-related fields, stellar astrophysics, and instrumentation related questions. These challenges likely stem from less abundant training data, limited historical context, and rapid recent developments in these areas. This pattern is observed across both open-weights and proprietary models, with regional dependencies evident, highlighting the impact of training data diversity on model performance in specialized scientific domains. Top-performing models demonstrate well-calibrated confidence, with correlations above 0.9 between confidence and correctness, though they tend to be slightly underconfident. The development for fast, low-cost inference of open-weights models presents new opportunities for affordable deployment in astronomy. The rapid progress observed suggests that LLM-driven research in astronomy may become feasible in the near future. © 2024, The Authors. All rights reserved.

关键词： Astrophysics

Multi-Modal Transformer for Accelerated MR Imaging

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arXiv 2021年

作者： Feng, Chun-Mei Yan, Yunlu Chen, Geng Xu, Yong Hu, Ying Shao, Ling Fu, Huazhu Shenzhen Key Laboratory of Visual Object Detection and Recognition Harbin Institute of Technology Shenzhen518055 China National Engineering Laboratory for Integrated AeroSpace-Ground-Ocean Big Data Application Technology School of Computer Science and Engineering Northwestern Polytechnical University Xi’an710072 China Terminus Group China Institute of High Performance Computing A*STAR Singapore138632 Singapore

Accelerated multi-modal magnetic resonance (MR) imaging is a new and effective solution for fast MR imaging, providing superior performance in restoring the target modality from its undersampled counterpart with guidance from an auxiliary modality. However, existing works simply combine the auxiliary modality as prior information, lacking in-depth investigations on the potential mechanisms for fusing different modalities. Further, they usually rely on the convolutional neural networks (CNNs), which is limited by the intrinsic locality in capturing the long-distance dependency. To this end, we propose a multi-modal transformer (MTrans), which is capable of transferring multi-scale features from the target modality to the auxiliary modality, for accelerated MR imaging. To capture deep multi-modal information, our MTrans utilizes an improved multi-head attention mechanism, named cross attention module, which absorbs features from the auxiliary modality that contribute to the target modality. Our framework provides three appealing benefits: (i) Our MTrans use an improved transformers for multi-modal MR imaging, affording more global information compared with existing CNN-based methods. (ii) A new cross attention module is proposed to exploit the useful information in each modality at different scales. The small patch in the target modality aims to keep more fine details, the large patch in the auxiliary modality aims to obtain high-level context features from the larger region and supplement the target modality effectively. (iii) We evaluate MTrans with various accelerated multi-modal MR imaging tasks, e.g., MR image reconstruction and super-resolution, where MTrans outperforms state-of-the-art methods on fastMRI and real-world clinical datasets. © 2021, CC BY.

关键词： Magnetic resonance imaging

Exploring Separable Attention for Multi-Contrast MR Image Super-Resolution

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arXiv 2021年

作者： Feng, Chun-Mei Yan, Yunlu Yu, Kai Xu, Yong Yang, Jian Shao, Ling Fu, Huazhu The Shenzhen Key Laboratory of Visual Object Detection and Recognition Harbin Institute of Technology Shenzhen518055 China The Institute of High Performance Computing A*STAR Singapore138632 Singapore The PCA Laboratory Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education Nanjing University of Science and Technology Nanjing210094 China The Jiangsu Key Laboratory of Image and Video Understanding for Social Security School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China Terminus Group China

Super-resolving the Magnetic Resonance (MR) image of a target contrast under the guidance of the corresponding auxiliary contrast, which provides additional anatomical information, is a new and effective solution for fast MR imaging. However, current multi-contrast super-resolution (SR) methods tend to concatenate different contrasts directly, ignoring their relationships in different clues, e.g., in the high-intensity and low-intensity regions. In this study, we propose a separable attention network (comprising high-intensity priority attention and low-intensity separation attention), named SANet. Our SANet could explore the areas of high-intensity and low-intensity regions in the "forward" and "reverse" directions with the help of the auxiliary contrast, while learning clearer anatomical structure and edge information for the SR of a target-contrast MR image. SANet provides three appealing benefits: (1) It is the first model to explore a separable attention mechanism that uses the auxiliary contrast to predict the high-intensity and low-intensity regions regions, diverting more attention to refining any uncertain details between these regions and correcting the fine areas in the reconstructed results. (2) A multi-stage integration module is proposed to learn the response of multi-contrast fusion at multiple stages, get the dependency between the fused representations, and boost their representation ability. (3) Extensive experiments with various state-of-the-art multi-contrast SR methods on fastMRI and clinical in vivo datasets demonstrate the superiority of our model. © 2021, CC BY.

关键词： Magnetic resonance imaging